Difference between revisions of "Fairness Without Demographics in Repeated Loss Minimization"
From statwiki
| Line 2: | Line 2: | ||
=Overview of the Paper= | =Overview of the Paper= | ||
| + | |||
| + | =Introduction= | ||
| + | |||
| + | ==Fairness== | ||
| + | |||
| + | =Example and Problem Setup= | ||
| + | |||
| + | =Disparity Amplification= | ||
Revision as of 14:16, 19 October 2018
This page contains the summary of the paper "Fairness Without Demographics in Repeated Loss Minimization" by Hashimoto, T. B., Srivastava, M., Namkoong, H., & Liang, P. which was published at the International Conference of Machine Learning (ICML) in 2018. In the following, an
